Quod Erat Demonstrandum (QED) is Latin for “that which had to be proven.” This abbreviation was traditionally used at the end of mathematical proofs to signal the completion of said proofs. I joined the Qatar Computing Research Institute (QCRI) well over 3 years ago with a very specific mission and mandate: to develop and deploy next generation humanitarian technologies. So I built the Institute’s Social Innovation Program from the ground up and recruited the majority of the full-time experts (scientists, engineers, research assistants, interns & project manager) who have become integral to the Program’s success. During these 3+years, my team and I partnered directly with humanitarian and development organizations to empirically prove that methods from advanced computing can be used to make sense of Big (Crisis) Data. The time has thus come to add “QED” to the end of that proof and move on to new adventures. But first a reflection.
Over the past 3.5 years, my team and I at QCRI developed free and open source solutions powered by crowdsourcing and artificial intelligence to make sense of Tweets, text messages, pictures, videos, satellite and aerial imagery for a wide range of humanitarian and development projects. We co-developed and co-deployed these platforms (AIDR and MicroMappers) with the United Nations and the World Bank in response to major disasters such as Typhoons Haiyan and Ruby, Cyclone Pam and both the Nepal & Chile Earthquakes. In addition, we carried out peer-reviewed, scientific research on these deployments to better understand how to meet the information needs of our humanitarian partners. We also tackled the information reliability question, experimenting with crowd-sourcing (Verily) and machine learning (TweetCred) to assess the credibility of information generated during disasters. All of these initiatives were firsts in the humanitarian technology space.
We later developed AIDR-SMS to auto-classify text messages; a platform that UNICEF successfully tested in Zambia and which the World Food Program (WFP) and the International Federation of the Red Cross (IFRC) now plan to pilot. AIDR was also used to monitor a recent election, and our partners are now looking to use AIDR again for upcoming election monitoring efforts. In terms of MicroMappers, we extended the platform (considerably) in order to crowd-source the analysis of oblique aerial imagery captured via small UAVs, which was another first in the humanitarian space. We also teamed up with excellent research partners to crowdsource the analysis of aerial video footage and to develop automated feature-detection algorithms for oblique imagery analysis based on crowdsourced results derived from MicroMappers. We developed these Big Data solutions to support damage assessment efforts, food security projects and even this wildlife protection initiative.
In addition to the above accomplishments, we launched the Internet Response League (IRL) to explore the possibility of leveraging massive multiplayer online games to process Big Crisis Data. Along similar lines, we developed the first ever spam filter to make sense of Big Crisis Data. Furthermore, we got directly engaged in the field of robotics by launching the Humanitarian UAV Network (UAViators), yet another first in the humanitarian space. In the process, we created the largest repository of aerial imagery and videos of disaster damage, which is ripe for cutting-edge computer vision research. We also spearheaded the World Bank’s UAV response to Category 5 Cyclone Pam in Vanuatu and also directed a unique disaster recovery UAV mission in Nepal after the devastating earthquakes. (I took time off from QCRI to carry out both of these missions and also took holiday time to support UN relief efforts in the Philippines following Typhoon Haiyan in 2013). Lastly, on the robotics front, we championed the development of international guidelines to inform the safe, ethical & responsible use of this new technology in both humanitarian and development settings. To be sure, innovation is not just about the technology but also about crafting appropriate processes to leverage this technology. Hence also the rationale behind the Humanitarian UAV Experts Meetings that we’ve held at the United Nations Secretariat, the Rockefeller Foundation and MIT.
All of the above pioneering-and-experimental projects have resulted in extensive media coverage, which has placed QCRI squarely on the radar of international humanitarian and development groups. This media coverage has included the New York Times, Washington Post, Wall Street Journal, CNN, BBC News, UK Guardian, The Economist, Forbes and Times Magazines, New Yorker, NPR, Wired, Mashable, TechCrunch, Fast Company, Nature, New Scientist, Scientific American and more. In addition, our good work and applied research has been featured in numerous international conference presentations and keynotes. In sum, I know of no other institute for advanced computing research that has contributed this much to the international humanitarian space in terms of thought-leadership, strategic partnerships, applied research and operational expertise through real-world co-deployments during and after major disasters.
There is, of course, a lot more to be done in the humanitarian technology space. But what we have accomplished over the past 3 years clearly demonstrates that techniques from advanced computing can indeed provide part of the solution to the pressing Big Data challenge that humanitarian & development organizations face. At the same time, as I wrote in the concluding chapter of my new book, Digital Humanitarians, solving the Big Data challenge does not alas imply that international aid organizations will actually make use of the resulting filtered data or any other data for that matter—even if they ask for this data in the first place. So until humanitarian organizations truly shift towards both strategic and tactical evidence-based analysis & data-driven decision-making, this disconnect will surely continue unabated for many more years to come.
Reflecting on the past 3.5 years at QCRI, it is crystal clear to me that the number one most important lesson I (re)learned is that you can do anything if you have an outstanding, super-smart and highly dedicated team that continually goes way above and beyond the call of duty. It is one thing for me to have had the vision for AIDR, MicroMappers, IRL, UAViators, etc., but vision alone does not amount to much. Implementing said vision is what delivers results and learning. And I simply couldn’t have asked for a more talented & stellar team to translate these visions into reality over the past 3+years. You each know who you are, partners included; it has truly been a privilege and honor working with you. I can’t wait to see what you do next at/with QCRI. Thank you for trusting me; thank you for sharing my vision; thanks for your sense of humor, and thank you for your dedication and loyalty to science and social innovation.
So what’s next for me? I’ll be lining up independent consulting work with several organizations (likely including QCRI). In short, I’ll be open for business. I’m also planning to work on a new project that I’m very excited about, so stay tuned for updates; I’ll be sure to blog about this new adventure when the time is right. For now, I’m busy wrapping up my work as Director of Social Innovation at QCRI and working with the best team there is. QED.
MAQSA: Social Analytics of User Responses to News
Designed by QCRI in partnership with MIT and Al-Jazeera, MAQSA provides an interactive topic-centric dashboard that summarizes news articles and user responses (comments, tweets, etc.) to these news items. The platform thus helps editors and publishers in newsrooms like Al-Jazeera’s better “understand user engagement and audience sentiment evolution on various topics of interest.” In addition, MAQSA “helps news consumers explore public reaction on articles relevant to a topic and refine their exploration via related entities, topics, articles and tweets.” The pilot platform currently uses Al-Jazeera data such as Op-Eds from Al-Jazeera English.
Given a topic such as “The Arab Spring,” or “Oil Spill”, the platform combines time, geography and topic to “generate a detailed activity dashboard around relevant articles. The dashboard contains an annotated comment timeline and a social graph of comments. It utilizes commenters’ locations to build maps of comment sentiment and topics by region of the world. Finally, to facilitate exploration, MAQSA provides listings of related entities, articles, and tweets. It algorithmically processes large collections of articles and tweets, and enables the dynamic specification of topics and dates for exploration.”
While others have tried to develop similar dashboards in the past, these have “not taken a topic-centric approach to viewing a collection of news articles with a focus on their user comments in the way we propose.” The team at QCRI has since added a number of exciting new features for Al-Jazeera to try out as widgets on their site. I’ll be sure to blog about these and other updates when they are officially launched. Note that other media companies (e.g., UK Guardian) will also be able to use this platform and widgets once they become public.
As always with such new initiatives, my very first thought and question is: how might we apply them in a humanitarian context? For example, perhaps MAQSA could be repurposed to do social analytics of responses from local stakeholders with respect to humanitarian news articles produced by IRIN, an award-winning humanitarian news and analysis service covering the parts of the world often under-reported, misunderstood or ignored. Perhaps an SMS component could also be added to a MAQSA-IRIN platform to facilitate this. Or perhaps there’s an application for the work that Internews carries out with local journalists and consumers of information around the world. What do you think?
Posted in Humanitarian Technologies, Social Computing, Social Media
Tagged Al-Jazeera, analysis, Comments, MAQSA, MIT, news, QCRI, Tweets, Users